diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/_add_newdocs.py | 19 |
1 files changed, 13 insertions, 6 deletions
diff --git a/numpy/core/_add_newdocs.py b/numpy/core/_add_newdocs.py index 0225d12b9..2f1273904 100644 --- a/numpy/core/_add_newdocs.py +++ b/numpy/core/_add_newdocs.py @@ -3953,15 +3953,22 @@ add_newdoc('numpy.core.multiarray', 'ndarray', ('tolist', Examples -------- - For a 1D array, ``a.tolist()`` is almost the same as ``list(a)``: + For a 1D array, ``a.tolist()`` is almost the same as ``list(a)``, + except that ``tolist`` changes numpy scalars to Python scalars: - >>> a = np.array([1, 2]) - >>> list(a) + >>> a = np.uint32([1, 2]) + >>> a_list = list(a) + >>> a_list [1, 2] - >>> a.tolist() + >>> type(a_list[0]) + <class 'numpy.uint32'> + >>> a_tolist = a.tolist() + >>> a_tolist [1, 2] + >>> type(a_tolist[0]) + <class 'int'> - However, for a 2D array, ``tolist`` applies recursively: + Additionally, for a 2D array, ``tolist`` applies recursively: >>> a = np.array([[1, 2], [3, 4]]) >>> list(a) @@ -4246,7 +4253,7 @@ add_newdoc('numpy.core.umath', 'frompyfunc', See Also -------- - vectorize : evaluates pyfunc over input arrays using broadcasting rules of numpy + vectorize : Evaluates pyfunc over input arrays using broadcasting rules of numpy. Notes ----- |